Properties and first application of an error-statistics tuning method in variational assimilation

The method for tuning observational or background error statistics is presented and some of its properties are exposed using theoretical considerations and experiments carried out in a simplified framework. In particular, the method is shown to be equivalent to a maximum-likelihood evaluation and its efficiency is seen to depend on the number of observations. The results of several experiments carried out with the variational assimilation system of the French numerical weather-prediction system ARPEGE, both with simulated and actual datasets involving satellite radiances, are also presented. The temporal stability of the results and their consistency with the known quality of the measurements are shown.